Anand V. Bodapati

A Direct Approach to Predicting Discretized Response in Target Marketing

A problem that occurs frequently in direct marketing is the prediction of the value of a discretizing function of a response variable. For example, to target consumers for a coupon mailing, a retail chain may want to predict whether a prospective customers grocery expenditures exceed a predetermined threshold. The current approach to this prediction problem is to model the response variable and then apply the discretizing function to the predicted value of the response variable. In contrast with this “indirect” approach, the authors propose a “direct” approach in which they model discretized values of the response variable. They show theoretically that the direct approach achieves better predictive performance than the commonly used indirect approach when the response model is misspecified and the sample size is large. These two conditions are commonly met in direct marketing situations. This result is counterintuitive because the direct approach entails “throwing away” information. However, although both the discretized response data and the continuous data provide biased predictions when a misspecified model is used, the lower information content of the discretized variable helps the bias be smaller. The authors demonstrate the performance of the proposed approach in a simulation experiment, a retail targeting application, and a customer satisfaction application. The key managerial implication of the result is that the current practice of restricting attention to models based on the indirect approach may be suboptimal. Target marketers should expand the set of candidate models to include models based on the proposed direct approach.

The Impact of Feature Advertising on Customer Store Choice

A heavily used competitive tactic in the grocery business is the weekly advertising of price reductions in newspaper inserts and store fliers. Store managers commonly believe that advertisements of price reductions and loss leaders help to build store traffic by diverting customers from competing stores, thereby increasing store volume and profitability. It is therefore not surprising that grocery retail planners across competing stores expend considerable thought on what items to advertise each week and at what levels of prominence. What is surprising, however, is that we marketing scientists do not know much about the manner and extent to which feature advertising in a competitive environment influences where and how customers shop. The marketing science literature has not even been able to establish that feature advertising has a substantial impact on store choice, let alone the more operational question of which categories are better at drawing consumers away from one store and into a competing store. In this paper we employ a stochastic choice modeling framework to propose and empirically estimate a disaggregate, consumer-level model of the effects of feature advertising on store choice. We use this model to understand which categories are more influential drivers of store traffic and better at diverting consumers from competing stores.

Parental Preference Assessment for Vesicoureteral Reflux Management in Children

Purpose: Parents of children with vesicoureteral reflux are presented with a variety of management options, which in many cases offer a similar risk‐benefit ratio. To facilitate shared decision making, parental preferences regarding vesicoureteral reflux treatment options need to be acknowledged. We aimed to characterize the clinical experience of parents and elicit core themes affecting decision making in regard to managing vesicoureteral reflux in their child. Materials and Methods: A semistructured, qualitative interview script was developed and vetted by 25 pediatric urologists to discuss treatment options for vesicoureteral reflux. Additional patient interviews were conducted until new themes failed to arise. Content analysis was performed to extract all statements that described treatment options. Similar statements were combined until a final list of unique themes emerged. Results: A total of 26 interviews were performed, yielding 689 statements about overall parent experiences with managing vesicoureteral reflux in the child and 450 statements (65%) pertaining to treatment options. Of the 13 themes that emerged, those most commonly considered were the prevention of future urinary tract infections by 85% of parents, the efficacy rate of treatment options by 85%, the burden of daily maintenance or compliance by 77%, antibiotic resistance by 69%, chronic kidney damage by 62% and invasiveness by 58%. Conclusions: Our study emphasizes that when choosing a treatment option for vesicoureteral reflux in their child, parent preferences regarding risks and benefits are variable. However, their chief concerns include whether a method decreases the risk of urinary tract infections, has an acceptable efficacy rate and aligns itself with the capabilities of the family. These themes help frame discussions between families and clinicians regarding vesicoureteral reflux management, and they can facilitate shared decision making.

Purchase-Frequency Bias in Random-Coefficients Brand-Choice Models

Conventional random-coefficients models of conditional brand choice using panel data ignore the dependence of the random-coefficients distribution on the purchase frequencies. We show that this leads to biased estimates and propose a conditional likelihood approach to obtain unbiased estimates. Unlike alternative approaches that require observation of “no-purchase” occasions, our proposed method relies only on purchase data. Furthermore, our approach does not require that the researcher specify the distribution of purchase frequencies. As a result, estimates of the brand-choice model are unaffected by misspecification of the model of purchase frequencies. We demonstrate the performance of the proposed approach in simulated data and in scanner data. We find that results differ substantively from the conventional latent-class model in terms of segment membership probabilities, segment characteristics, and price elasticities.

Habits and Free Associations: Free Your Mind but Mind Your Habits

Most consumer choices are repeat choices driven by habits. Psychological accounts of habits have generally emphasized the driving role of external factors, especially contextual cues, in habit performance. The present research investigates the influence of an individual-difference variable that reflects a more internal driver of habits. Three studies reveal a negative relationship between people’s tendency to generate relatively uncommon word responses in free-association tasks and their tendency to repeat choice behavior across different consumer contexts. These results implicate free associations as having a role in habit performance and inform practical research on predictors of consumers’ repeat choices.